Bibliographic record
Abstract
This introductory paper offers insights into the importance of care work for wellbeing, introducing key themes evident in this special issue that span the theoretical and empirical boundaries of care and paid work for wellbeing. The focus is predominately on caring for adults, whether dependent adult children, spouses, or elderly family members/friends. These key themes, which span both time and space, are as follows: scaled relations of care work for the production of wellbeing; roles, power and influence of intersectional identities on the wellbeing of carer-employees, and; employment interventions to support opportunities for care and wellbeing. In totality, these three themes point to a common question: how can care responsibilities be more equally shared? Addressing this question is complex since care work spans multiple scales, from family units through to country-specific collective norms, and across international policy. It also begs the question of how to best sustain the four primary groups of supports implicated in care work, including: unpaid carers, such as family, friends, and neighbours; community supports and services provided by non-profits and the voluntary sector; state/government supports, such as paid leaves or employment insurance for carers, and; employers of unpaid carers. The geographical scope of the papers contained in the special issue span from international country comparisons of unpaid care work, through to transnational experiences across two or more countries, through to case studies situated in two of Canada's largest provinces. Building on the three key themes, strategies are proposed to inform the development of sustainable care systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.019 |
| Scholarly communication | 0.018 | 0.009 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".